This chapter proposes a novel Quantum Intelligence (QI)-based optimized,
secure, and intelligent architectures for the IoT-based VANETs, known as Internet
of Vehicles (IoV). Such technologies range from general Quantum Intelligence, AI,
ML, and DL, through to the specific architectures upon which these solutions may be
based, including ANN and the Levenberg Neural Engine as examples. The first
proposed architecture, known as Quantum Intelligence-Driven Cluster-Based Adaptive
Intelligence (QI-CAI), represents a core contribution in enhancing IoV communication
by enabling dynamic and efficient clustering through the integration of Internet of
Things (IoT) enabled intelligent services within the combined framework.
In continuity, the second proposed architecture, Fine-Tuned Deep Learning Security
with Quantum Intelligence (FDS-QI) Model, for improve security and avoid cyberattacks. Together, these two architectures form a unified framework that addresses both
communication efficiency and security in next-generation IoV systems.
Keywords: AI-driven security, Clustering architecture, Deep learning models, Internet of vehicles (IoV), Quantum computing, Quantum-enhanced security, Quantum intelligence (QI), Quantum optimization, Real-time security, Secure communication, Security frameworks, Vehicle networks, Vehicle security systems.
